Cloud/Data Operations Engineer

Cloud / Data Operations Engineer
About Us
Human Loops is a Physical AI operations company supporting global AI, robotics, and technology companies through data collection, annotation, validation, teleoperation, and Human-in-the-Loop (HITL) services. Our operations team plays a key role in delivering high-quality datasets while maintaining speed, accuracy, and operational excellence.
We are early stage startup, growing rapidly out of Nagpur, building a New-Age Company catering to the AI Companies at the forefront of this technology revolution. We are looking for Engineers with very seen interest in Data, Cloud and AI Tools. You musn't be an expert but a very very quick learner, eager to grow and grasp a lot.
About The Role
We move roughly 500TB of client data every month. Field teams across multiple sites capture egocentric and multimodal video daily; it lands on our local servers, gets verified and organized, and ships to client cloud buckets. You own that path.
This is a hands-on engineering role, not a support desk. You'll spend your time in a terminal, writing scripts that remove manual work, and diagnosing why a transfer is running at half the speed it should.
What You'll Do
Manage local ingest infrastructure — staging servers, card-reader stations, NAS storage
Design and maintain cloud bucket and prefix structure for client data, with correct access isolation between clients
Build and run automated upload pipelines — resumable, parallel, bandwidth-aware, with verification and alerting
Write Python and Bash tooling to enforce naming conventions, organize captures, verify integrity, and generate reports
Maintain a catalogue of every capture: site, date, task type, employee, size, upload and delivery status
Monitor storage capacity, disk health, and network throughput; plan ahead of growth
Diagnose performance bottlenecks across disk, filesystem, and network
Document runbooks so operations can run daily ingest without escalating
Required
3+ years in cloud operations, infrastructure, or data engineering
Strong Linux command-line ability — you work terminal-first, no GUI dependency
Solid Bash scripting
Python for automation — real working code, not copy-pasted snippets
Object storage in production: AWS S3 or equivalent (GCS, OCI) — bucket and prefix design, IAM, lifecycle policy, storage classes
Practical networking sense: throughput testing, and the ability to work out whether a slow transfer is the disk, the network, or the script
Large file transfer tooling: rclone, rsync, or cloud CLIs, including resumable and parallel transfers
Fluent with AI coding tools (Claude, ChatGPT, Cursor, Copilot) — we expect you to use them to work faster, and to check their output
Preferred
AWS certification (Solutions Architect Associate, SysOps Administrator, or Cloud Practitioner)
Storage fundamentals: RAID, ZFS/XFS, SMART monitoring
Basic SQL for building a data catalogue
Video file handling — ffmpeg, container formats
Monitoring tools (Prometheus, Grafana)
Not Required
Windows Server administration, helpdesk or ticketing experience, ERP support.
Why this role
You'll have a critical role in infrastructure carrying half a petabyte a month for global AI labs, in a company where the data pipeline is the product — not a cost centre. Direct access to the Chief AI Officer, and real authority over how this is built.
Skills: data,storage,cloud

Work arrangement
No